What is associated with race performance in male 100-km ultra-marathoners--anthropometry, training or marathon best time?

We investigated the associations of anthropometry, training, and pre-race experience with race time in 93 recreational male ultra-marathoners (mean age 44.6 years, s = 10.0; body mass 74.0 kg, s = 9.0; height 1.77 m, s = 0.06; body mass index 23.4 kg · m(-2), s = 2.0) in a 100-km ultra-marathon using bivariate and multivariate analysis. In the bivariate analysis, body mass index (r = 0.24), the sum of eight skinfolds (r = 0.55), percent body fat (r = 0.57), weekly running hours (r = -0.29), weekly running kilometres (r = -0.49), running speed during training (r = -0.50), and personal best time in a marathon (r = 0.72) were associated with race time. Results of the multiple regression analysis revealed an independent and negative association of weekly running kilometres and average speed in training with race time, as well as a significant positive association between the sum of eight skinfold thicknesses and race time. There was a significant positive association between 100-km race time and personal best time in a marathon. We conclude that both training and anthropometry were independently associated with race performance. These characteristics remained relevant even when controlling for personal best time in a marathon.     

Similarities and differences in anthropometry and training between recreational male 100-km ultra-marathoners and marathoners

Abstract Several recent investigations showed that the best marathon time of an individual athlete is also a strong predictor variable for the race time in a 100-km ultra-marathon. We investigated similarities and differences in anthropometry and training characteristics between 166 100-km ultra-marathoners and 126 marathoners in recreational male athletes. The association of anthropometric variables and training characteristics with race time was assessed by using bi- and multi-variate analysis. Regarding anthropometry, the marathoners had a significantly lower calf circumference (P?相似文献   

A comparison of anthropometric and training characteristics of Ironman triathletes and Triple Iron ultra-triathletes

Abstract

We examined differences in anthropometry and training between 64 Triple Iron ultra-triathletes competing over 11.4 km swimming, 540 km cycling, and 126.6 km running, and 71 Ironman triathletes competing over 3.8 km swimming, 180 km cycling, and 42.2 km running. The association of anthropometry and training with race time was investigated using multiple linear regression analysis. The Triple Iron ultra-triathletes were smaller (P < 0.05), had shorter limbs (P < 0.05), a higher body mass index (P < 0.05), and larger limb circumferences (P < 0.01) than the Ironman triathletes. The Triple Iron ultra-triathletes trained for more hours (P < 0.01) and covered more kilometres (P < 0.01), but speed in running during training was slower compared with the Ironman triathletes (P < 0.01). For Triple Iron ultra-triathletes, percent body fat (P = 0.022), training volume per week (P < 0.0001), and weekly kilometres in both cycling (P < 0.0001) and running (P < 0.0001) were related to race time. For Ironman triathletes, percent body fat (P < 0.0001), circumference of upper arm (P = 0.006), and speed in cycling training (P = 0.012) were associated with total race time. We conclude that both Triple Iron ultra-triathletes and Ironman triathletes appeared to profit from low body fat. Triple Iron ultra-triathletes relied more on training volume in cycling and running, whereas speed in cycling training was related to race time in Ironman triathletes.     

A comparison of anthropometric and training characteristics of Ironman triathletes and Triple Iron ultra-triathletes

We examined differences in anthropometry and training between 64 Triple Iron ultra-triathletes competing over 11.4 km swimming, 540 km cycling, and 126.6 km running, and 71 Ironman triathletes competing over 3.8 km swimming, 180 km cycling, and 42.2 km running. The association of anthropometry and training with race time was investigated using multiple linear regression analysis. The Triple Iron ultra-triathletes were smaller (P < 0.05), had shorter limbs (P < 0.05), a higher body mass index (P < 0.05), and larger limb circumferences (P < 0.01) than the Ironman triathletes. The Triple Iron ultra-triathletes trained for more hours (P < 0.01) and covered more kilometres (P < 0.01), but speed in running during training was slower compared with the Ironman triathletes (P < 0.01). For Triple Iron ultra-triathletes, percent body fat (P = 0.022), training volume per week (P < 0.0001), and weekly kilometres in both cycling (P < 0.0001) and running (P < 0.0001) were related to race time. For Ironman triathletes, percent body fat (P < 0.0001), circumference of upper arm (P = 0.006), and speed in cycling training (P = 0.012) were associated with total race time. We conclude that both Triple Iron ultra-triathletes and Ironman triathletes appeared to profit from low body fat. Triple Iron ultra-triathletes relied more on training volume in cycling and running, whereas speed in cycling training was related to race time in Ironman triathletes.     

Field and laboratory correlates of performance in competitive cross-country mountain bikers

Abstract

We designed a laboratory test with variable fixed intensities to simulate cross-country mountain biking and compared this to more commonly used laboratory tests and mountain bike performance. Eight competitive male mountain bikers participated in a cross-country race and subsequently did six performance tests: an individual outdoor time trial on the same course as the race and five laboratory tests. The laboratory tests were as follows: an incremental cycle test to fatigue to determine peak power output; a 26-min variable fixed-intensity protocol using an electronically braked ergometer followed immediately by a 1-km time trial using the cyclist's own bike on an electronically braked roller ergometer; two 52-min variable fixed-intensity protocols each followed by a 1-km time trial; and a 1-km time trial done on its own. Outdoor competition time and outdoor time trial time correlated significantly (r = 0.79, P < 0.05). Both outdoor tests correlated better with peak power output relative to body mass (both r = ?0.83, P < 0.05) than absolute peak power output (outdoor competition: r = ?0.65; outdoor time trial: r = ?0.66; non-significant). Outdoor performance times did not correlate with the laboratory tests. We conclude that cross-country mountain biking is similar to uphill or hilly road cycling. Further research is required to design sport-specific tests to determine the remaining unexplained variance in performance.     

A faster running speed is associated with a greater body weight loss in 100-km ultra-marathoners

Abstract

In 219 recreational male runners, we investigated changes in body mass, total body water, haematocrit, plasma sodium concentration ([Na⁺]), and urine specific gravity as well as fluid intake during a 100-km ultra-marathon. The athletes lost 1.9 kg (s = 1.4) of body mass, equal to 2.5% (s = 1.8) of body mass (P < 0.001), 0.7 kg (s = 1.0) of predicted skeletal muscle mass (P < 0.001), 0.2 kg (s = 1.3) of predicted fat mass (P < 0.05), and 0.9 L (s = 1.6) of predicted total body water (P < 0.001). Haematocrit decreased (P < 0.001), urine specific gravity (P < 0.001), plasma volume (P < 0.05), and plasma [Na⁺] (P < 0.05) all increased. Change in body mass was related to running speed (r = ?0.16, P < 0.05), change in plasma volume was associated with change in plasma [Na⁺] (r = ?0.28, P < 0.0001), and change in body mass was related to both change in plasma [Na⁺] (r = ?0.36) and change in plasma volume (r = 0.31) (P < 0.0001). The athletes consumed 0.65 L (s = 0.27) fluid per hour. Fluid intake was related to both running speed (r = 0.42, P < 0.0001) and change in body mass (r = 0.23, P = 0.0006), but not post-race plasma [Na⁺] or change in plasma [Na⁺] (P > 0.05). In conclusion, faster runners lost more body mass, runners lost more body mass when they drank less fluid, and faster runners drank more fluid than slower runners.     

Relationships among field-test measures and physical match performance in elite-standard soccer referees

Abstract

The aim of this study was to assess the extent to which measures derived from the new FIFA referees’ fitness tests can be used to monitor a referee's match-related physical capacity. Match-analysis data were collected (Prozone®, Leeds, UK) from 17 soccer referees for 5.0 (s = 1.7) FA Premier League matches per referee during the first 4 months of the 2007–08 season. Physical match performance categories included total distance covered, high-intensity running distance (speed >5.5 m · s^?1), and sprinting distance (>7.0 m · s^?1). The two tests were a 6 × 40-m sprint test and a 150-m interval test. Heart rate demand was correlated with total match distance covered (r = ?0.70, P = 0.002) and high-intensity running (r = ?0.57, P = 0.018) in the interval test. The fastest 40-m sprint was related to total distance covered (r = ?0.69, P = 0.002), high-intensity running (r = ?0.76, P < 0.001), and sprinting distance (r = ?0.75, P = 0.001), while mean time for the 40-m sprints was related to total distance covered (r = ?0.70, P = 0.002), high-intensity running (r = ?0.77, P < 0.001), and sprinting distance (r = ?0.77, P < 0.001). The referees who recorded the best interval-test heart rate demand and fastest 40-m time produced the best physical match performances. However, only the sprint test and in particular the fastest 40-m time had appropriate construct validity for the physical assessment of soccer referees.     

Dissociation between running economy and running performance in elite Kenyan distance runners

The purpose of this study was to investigate the relationship between running economy (RE) and performance in a homogenous group of competitive Kenyan distance runners. Maximal aerobic capacity (VO_2max) (68.8 ± 3.8 ml?kg^?1?min^?1) was determined on a motorised treadmill in 32 Kenyan (25.3 ± 5.0 years; IAAF performance score: 993 ± 77 p) distance runners. Leg anthropometry was assessed and moment arm of the Achilles tendon determined. While Achilles moment arm was associated with better RE (r² = 0.30, P = 0.003) and upper leg length, total leg length and total leg length to body height ratio were correlated with running performance (r = 0.42, P = 0.025; r = 0.40, P = 0.030 and r = 0.38, P = 0.043, respectively), RE and maximal time on treadmill (t_max) were not associated with running performance (r = ?0.01, P = 0.965; r = 0.27; P = 0.189, respectively) in competitive Kenyan distance runners. The dissociation between RE and running performance in this homogenous group of runners would suggest that RE can be compensated by other factors to maintain high performance levels and is in line with the idea that RE is only one of many factors explaining elite running performance.     

Marathon performance but not BMI affects post-marathon pro-inflammatory and cartilage biomarkers

We tested the hypothesis that changes in serum cartilage oligomeric matrix protein (COMP), tumour necrosis factor α (TNF-α), interleukin-6 (IL-6) and high-sensitivity C-reactive protein (hsCRP) concentration after regular endurance training and running a marathon race depend on body mass index (BMI) and/or on marathon performance. Blood samples were collected from 45 runners of varying BMI and running experience before and after a 10-week marathon training programme and before, immediately and 24 h after a marathon race. Serum biomarker concentrations, BMI and marathon finishing time were measured. The mean (95% confidence interval (CI)) changes from before to immediately after the marathon were COMP: 4.09 U/L (3.39–4.79 U/L); TNF-α: ?1.17 mg/L (?2.58 to 0.25 mg/L); IL-6: 12.0 pg/mL (11.4–12.5 pg/mL); and hsCRP: ?0.08 pg/mL (?0.14 to ?0.3 pg/mL). The mean (95% CI) changes from immediately after to 24 h after the marathon were COMP: 0.35 U/L (?0.88 to 1.57 U/L); TNF-α: ?0.43 mg/L (?0.99 to 0.13 mg/L); IL-6: ?9.9 pg/mL (?10.5 to ?9.4 pg/mL); and hsCRP: 1.52 pg/mL (1.25–1.79 pg/mL). BMI did not affect changes in biomarker concentrations. Differences in marathon finishing time explained 32% of variability in changes in serum hsCRP and 28% of variability in changes in serum COMP during the 24 h recovery after the marathon race (P < 0.001). Slower marathon finishing time but not a higher BMI modulates increases in pro-inflammatory markers or cartilage markers following a marathon race.     

Optimization of Maximal Rate of Heart Rate Increase Assessment in Runners

Purpose: Correlations between fatigue-induced changes in exercise performance and maximal rate of heart rate (HR) increase (rHRI) may be affected by exercise intensity during assessment. This study evaluated the sensitivity of rHRI for tracking performance when assessed at varying exercise intensities. Method: Performance (time to complete a 5-km treadmill time-trial [5TTT]) and rHRI were assessed in 15 male runners following 1 week of light training, 2 weeks of heavy training (HT), and a 10-day taper (T). Maximal rate of HR increase (measured in bpm·s^?1) was the first derivative maximum of a sigmoidal curve fit to HR data recorded during 5 min of running at 8 km·h^?1 (rHRI_8km·h^?1), and during subsequent transition to 13 km·h^?1 (rHRI_{8–13km·h^?1}) for a further 5 min. Results: Time to complete a 5-km treadmill time-trial was likely slower following HT (effect size ± 90% confidence interval = 0.16 ± 0.06), and almost certainly faster following T (–0.34 ± 0.08). Maximal rate of HR increase during 5 min of running at 8 km·h^?1 and rHRI_{8–13km·h^?1} were unchanged following HT and likely increased following T (0.77 ± 0.45 and 0.66 ± 0.62, respectively). A moderate within-individual correlation was found between 5TTT and rHRI_8km·h^?1 (r value ± 90% confidence interval = –.35 ± .32). However, in a subgroup of athletes (n = 7) who were almost certainly slower to complete the 5TTT (4.22 ± 0.88), larger correlations were found between the 5TTT and rHRI_8km·h^?1 (r = –.84 ± .22) and rHRI_{8–13km·h^?1} (r = –.52 ± .41). Steady-state HR during rHRI assessment in this group was very likely greater than in the faster subgroup (≥ 1.34 ± 0.86). Conclusion(s): The 5TTT performance was tracked by both rHRI_8km·h^?1 and rHRI_{8–13km·h^?1}. Correlations between rHRI and performance were stronger in a subgroup of athletes who exhibited a slower 5TTT. Individualized workloads during rHRI assessment may be required to account for varying levels of physical conditioning.     

The effects of work:rest duration on physiological and perceptual responses during intermittent exercise and performance

Abstract

In this study, we examined the effects of different work:rest durations during 20 min intermittent treadmill running and subsequent performance. Nine males (mean age 25.8 years, s = 6.8; body mass 73.9 kg, s = 8.8; stature 1.75 m, s = 0.05; [Vdot]O_2max 55.5 ml · kg^?1 · min^?1, s = 5.8) undertook repeated sprints at 120% of the speed at which [Vdot]O_2max was attained interspersed with passive recovery. The work:rest ratio was constant (1:1.5) with trials involving either short (6:9 s) or long (24:36 s) work:rest exercise protocols (total exercise time 8 min). Each trial was followed by a performance run to volitional exhaustion at the same running speed. Testing order was randomized and counterbalanced. Heart rate, oxygen consumption, respiratory exchange ratio, and blood glucose were similar between trials (P > 0.05). Blood lactate concentration was greater during the long than the short exercise protocol (P < 0.05), whereas blood pH was lower during the long than the short exercise protocol (7.28, s = 0.11 and 7.30, s = 0.03 at 20 min, respectively; P < 0.05). Perceptions of effort were greater throughout exercise for the long than the short exercise protocol (16.6, s = 1.4 and 15.1, s = 1.6 at 20 min, respectively; P < 0.05) and correlated with blood lactate (r = 0.43) and bicarbonate concentrations (r = ?0.59; P < 0.05). Although blood lactate concentration at 20 min was related to performance time (r = ?0.56; P < 0.05), no differences were observed between trials for time to exhaustion (short exercise protocol: 95.8 s, s = 30.0; long exercise protocol: 92.0 s, s = 37.1) or physiological responses at exhaustion (P > 0.05). Our results demonstrate that 20 min of intermittent exercise involving a long work:rest duration elicits greater metabolic and perceptual strain than intermittent exercise undertaken with a short work:rest duration but does not affect subsequent run time to exhaustion.     

Muscle damage and soreness following a 50-km cross-country ski race

Abstract

In this study, we examined indirect markers of muscle damage and muscle soreness following a 50-km cross-country ski race completed in 2 h and 57 min to 5 h and 9 min by 11 moderately trained male university students. Maximal strength of the knee extensors, several blood markers of muscle damage and inflammation, and muscle soreness (visual analog scale: 0 = “no pain”, 50 mm = “unbearably painful”) were measured one day before, immediately after, and 24, 48, 72, and 144 h after the race. Changes in the measures over time were analysed using one-way repeated-measures analysis of variance and a Fisher's post-hoc test. Maximal strength of the knee extensors decreased significantly (P<0.05) immediately after the race (mean ?27%, s=6), but returned to pre-exercise values within 24 h of the race. All blood markers increased significantly (P<0.05) following the race, peaking either immediately (lactate dehydrogenase: 253.7 IU · l^?1, s=13.3; myoglobin: 476.4 ng · ml^?1, s=85.5) or 24 h after the race (creatine kinase: 848.0 IU · l^?1, s=151.9; glumatic oxaloacetic transaminase: 44.3 IU · l^?1, s=4.2; aldolase: 10.0 IU · l^?1, s=1.3; C-reactive protein: 0.36 IU · l^?1, s=0.08). Muscle soreness developed in the leg, arm, shoulder, back, and abdomen muscles immediately after the race (10–30 mm), but decreased after 24 h (<15 mm), and disappeared 48 h after the race. These results suggest that muscle damage induced by a 50-km cross-country ski race is mild and recovery from the race does not take long.     

Effects of a minimalist shoe on running economy and 5-km running performance

The purpose of this study was to determine if minimalist shoes improve time trial performance of trained distance runners and if changes in running economy, shoe mass, stride length, stride rate and footfall pattern were related to any difference in performance. Twenty-six trained runners performed three 6-min sub-maximal treadmill runs at 11, 13 and 15 km·h^?1 in minimalist and conventional shoes while running economy, stride length, stride rate and footfall pattern were assessed. They then performed a 5-km time trial. In the minimalist shoe, runners completed the trial in less time (effect size 0.20 ± 0.12), were more economical during sub-maximal running (effect size 0.33 ± 0.14) and decreased stride length (effect size 0.22 ± 0.10) and increased stride rate (effect size 0.22 ± 0.11). All but one runner ran with a rearfoot footfall in the minimalist shoe. Improvements in time trial performance were associated with improvements in running economy at 15 km·h^?1 (r = 0.58), with 79% of the improved economy accounted for by reduced shoe mass (P < 0.05). The results suggest that running in minimalist shoes improves running economy and 5-km running performance.     

Effects of tapering on physical match activities in professional soccer players

ABSTRACT

This study aimed to examine: (i) the effect of decreasing training load (TL) during taper weeks on physical match activities in professional soccer players, and (ii) to disclose the relationship between weekly TL and physical match activities. Rating of perceived exertion was collected after each training session and match to quantify the TL in 19 professional players over 17 standard and 7 taper weeks during the season. Physical match activities were quantified by a computerised match analysis system and compared between standard training and taper weeks. Compared to standard weeks, the duration and frequency of training sessions during the taper weeks decreased (?21.7% and ?18.8%, respectively; P < 0.01) with no change in intensity (?4.8%; P = 0.09). Consequently, the weekly TL decreased during the taper weeks (?25.5%; P < 0.01). Increases in distance covered by intense running (+15.1%; P < 0.05), high-intensity running (HIR) (+15.7%; P < 0.01), number of sprints (+17.8%; P < 0.05) and number of high-speed runs (+15.7%; P < 0.05) were observed during the seven matches played after the taper weeks. High relationships were observed between TL and HIR distance covered, number of HIR and number of sprints (r = ?0.53; r = ?0.55; r = ?0.65, respectively; P < 0.01). Decreasing TL during taper weeks by reducing training duration and frequency but maintaining intensity was associated with an increase in physical activities during matches. However, it needs to be determined whether tapering or other match factors led to the changes in match activity.     

Moderate-domain pulmonary oxygen uptake kinetics and endurance running performance

Abstract

The aims of this study were to determine if the primary time constant (τ) for oxygen uptake ([Vdot]O₂) at the onset of moderate-intensity treadmill exercise is related to endurance running performance, and to establish if τ could be considered a determinant of endurance running performance. Thirty-six endurance trained male runners performed a series of laboratory tests, on separate days, to determine maximal oxygen uptake ([Vdot]O_2max), the ventilatory threshold (V_T) and running economy. In addition, runners completed six transitions from walking (4 km · h^?1) to moderate-intensity running (80% V_T) for the determination of the [Vdot]O₂ primary time constant and mean response time. During all tests, pulmonary gas-exchange was measured breath-by-breath. Endurance running performance was determined using a treadmill 5-km time-trial, after which runners were considered as combined performers (n=36) and, using a ranking system, high performers (n=10) and low performers (n=10). Relationships between τ and endurance running performance were quantified using correlation coefficients (r). Stepwise multiple regression was used to determine the primary predictor variables of endurance running performance in combined performers. Moderate correlations were observed between τ, mean response time and endurance running performance, but only for the combined performers (r=?0.55, P=0.001 and r=?0.50, P=0.002, respectively). The regression model for predicting 5-km performance did not include τ or mean response time. The velocity at [Vdot]O_2max was strongly correlated to endurance running performance in all groups (r=0.72 – 0.84, P < 0.01) and contributed substantially to the prediction of performance. In conclusion, the results suggest that despite their role in determining the oxygen deficit and having a moderate relationship with endurance running performance, neither τ nor mean response time is a primary determinant of endurance running performance.     

Relationships between physiological,anthropometric, and skill qualities and playing performance in professional rugby league players

Abstract

In this study, we investigated the relationship between physiological, anthropometric, and skill qualities and playing performance in professional rugby league players. Fifty-eight high-performance rugby league players underwent measurements for anthropometry (height, body mass, sum of seven skinfolds), physiological (speed, change of direction speed, lower body muscular power, repeated-sprint ability, prolonged high-intensity intermittent running ability, and estimated maximal aerobic power), technical skill (tackling proficiency, draw and pass proficiency), and perceptual skill (reactive agility, pattern recall, pattern prediction) qualities. National Rugby League matches were coded for attacking (e.g. line breaks, try assists, etc.) and defensive (e.g. missed tackles, tackling efficiency, etc.) statistics commonly used to assess rugby league playing performance. The number of line break assists was significantly associated (P < 0.05) with greater playing experience (r = 0.36), dual-task draw and pass proficiency (r = 0.54), reactive agility (r = 0.29), and pattern recall (r = 0.32) and prediction (r = 0.28) ability, while faster speed over 40 m (r = ?0.42) was associated (P < 0.05) with a higher number of tries scored. Greater age and playing experience, better lower body muscular power, and faster 10 m and 40 m speed were significantly associated (P < 0.05) with the number of tackle attempts (positive), tackles completed (positive), and proportion of missed tackles (negative). These findings demonstrate that well-developed physical and skill qualities are associated with effective playing performance in National Rugby League players.     

Physiological intensity profile,exercise load and performance predictors of a 65-km mountain ultra-marathon

The aims of the study were to describe the physiological profile of a 65-km (4000-m cumulative elevation gain) running mountain ultra-marathon (MUM) and to identify predictors of MUM performance. Twenty-three amateur trail-runners performed anthropometric evaluations and an uphill graded exercise test (GXT) for VO_2max, ventilatory thresholds (VTs), power outputs (PMax, PVTs) and heart rate response (HRmax, HR@VTs). Heart rate (HR) was monitored during the race and intensity was expressed as: Zone I (VT2) for exercise load calculation (training impulse, TRIMP). Mean race intensity was 77.1%±4.4% of HRmax distributed as: 85.7%±19.4% Zone I, 13.9%±18.6% Zone II, 0.4%±0.9% Zone III. Exercise load was 766±110 TRIMP units. Race time (11.8±1.6h) was negatively correlated with VO_2max (r = ?0.66, P <0.001) and PMax (r = ?0.73, P <0.001), resulting these variables determinant in predicting MUM performance, whereas exercise thresholds did not improve performance prediction. Laboratory variables explained only 59% of race time variance, underlining the multi-factorial character of MUM performance. Our results support the idea that VT1 represents a boundary of tolerable intensity in this kind of events, where exercise load is extremely high. This information can be helpful in identifying optimal pacing strategies to complete such extremely demanding MUMs.     

Gastrointestinal distress is common during a 161-km ultramarathon

This study examined the incidence, severity, and timing of gastrointestinal (GI) symptoms in finishers and non-finishers of the 161-km Western States Endurance Run. A total of 272 runners (71.0% of starters) completed a post-race questionnaire that assessed the incidence and severity (none = 0, mild = 1, moderate = 2, severe = 3, very severe = 4) of 12 upper (reflux/heartburn, belching, stomach bloating, stomach cramps/pain, nausea, vomiting) and lower (intestinal cramps/pain, flatulence, side ache/stitch, urge to defecate, loose stool/diarrhoea, intestinal bleeding/bloody faeces) GI symptoms experienced during each of four race segments. GI symptoms were experienced by most runners (96.0%). Flatulence (65.9% frequency, mean value 1.0, s = 0.6 severity), belching (61.3% frequency, mean value 1.0, s = 0.6 severity), and nausea (60.3% frequency, mean value 1.0, s = 0.7 severity) were the most common symptoms. Among race finishers, 43.9% reported that GI symptoms affected their race performance, with nausea being the most common symptom (86.0%). Among race non-finishers, 35.6% reported that GI symptoms were a reason for dropping out of the race, with nausea being the most common symptom (90.5%). For both finishers and non-finishers, nausea was greatest during the most challenging and hottest part of the race. GI symptoms are very common during ultramarathon running, and in particular, nausea is the most common complaint for finishers and non-finishers.     

Vertical stiffness and muscle strain in professional Australian football

Abstract

The purpose of this study was to establish if vertical stiffness was greater in professional Australian rules footballers who sustained a lower limb skeletal muscle strain compared to those who did not, and to establish if a relationship between age, or training history, and vertical stiffness existed. Thirty-one participants underwent weekly rebound jump testing on a force platform over two seasons. Vertical stiffness was calculated for injured players and the uninjured cohort 1 and 3 weeks prior to sustaining an injury and at the end of preseason. Eighteen athletes were in the “uninjured” cohort and 13 in the “injured” cohort. No significant difference in vertical stiffness was observed between groups (P = 0.18 for absolute stiffness; P = 0.08 for stiffness relative to body mass), within groups (P = 0.83 and P = 0.88, respectively) or for a time*cohort interaction (P = 0.77 and P = 0.80, respectively). No relationship between age and vertical stiffness existed (r = ?0.06 for absolute and relative stiffness), or training history and vertical stiffness (r = ?0.01 and 0.00 for absolute and relative stiffness, respectively) existed. These results and others lend to suggest that vertical stiffness is not related to lower limb muscle strain injury.     

Markers of isometric training intensity and reductions in resting blood pressure

Abstract

In this study, we examined the correlations between selected markers of isometric training intensity and subsequent reductions in resting blood pressure. Thirteen participants performed a discontinuous incremental isometric exercise test to volitional exhaustion at which point mean torque for the final 2-min stage (2min-torque_peak) and peak heart rate peak (HR_peak) were identified. Also, during 4 weeks of training (3 sessions per week, comprising 4 × 2 min bilateral leg isometric exercise at 95% HR_peak), heart rate (HR_train), torque (Torque_train), and changes in EMG amplitude (ΔEMG_amp) and frequency (ΔEMG_freq) were determined. The markers of training intensity were: Torque_train relative to the 2min-torque_peak (%2min-torque_peak), EMG relative to EMG_peak (%EMG_peak), HR_train ΔEMG_amp, ΔEMG_freq, and %MVC. Mean systolic (?4.9 mmHg) and arterial blood pressure (?2.7mmHg) reductions correlated with %2min-torque_peak (r = ?0.65, P = 0.02 and r = ?0.59, P = 0.03), ΔEMG_amp (r = 0.66, P = 0.01 and r = 0.59, P = 0.03), ΔEMG_freq (r = ?0.67, P = 0.01 and r = ?0.64, P = 0.02), and %EMG_peak (systolic blood pressure only; r = ?0.63, P = 0.02). These markers best reflect the association between isometric training intensity and reduction in resting blood pressure observed after bilateral leg isometric exercise training.